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By launching their internal agent in a single company-wide Slack channel, Perplexity enabled employees to see each other's prompts and use cases. This created a powerful cross-pollination of ideas and accelerated learning on how to best leverage the new tool for collaborative work.
At Stripe, engineers now collaborate on crafting the perfect prompt to guide AI agents. This new form of teamwork focuses on articulating the problem clearly and providing the right context, rather than co-writing code line-by-line. This can involve other engineers, data sources, or even other agents.
Beyond individual productivity, a shared AI tool fosters collaboration. Marketers can share effective prompts and custom GPTs, creating a living repository of best practices. This turns the tool into a third space for team communication, alongside Slack and email.
At Cursor, development is increasingly happening in Slack channels. Team members collectively kick off and redirect a cloud agent in a thread, turning development into a collaborative discussion. The IDE becomes a secondary tool, while communication platforms become the primary surface.
Most AI tools are single-player experiences. Linear is designing its agent sessions to be shared, collaborative spaces. Multiple people, like a PM and a designer, can jump into the same chat with an agent, see its work, and give it feedback together, collapsing the collaboration loop.
Using AI agents in shared Slack channels transforms coding from a solo activity into a collaborative one. Multiple team members can observe the agent's work, provide corrective feedback in the same thread, and collectively guide the task to completion, fostering shared knowledge.
By building internal AI agents directly into Slack, their usage becomes public and visible. This visibility is key for driving adoption; seeing a bot turn a message into a PR creates a "holy shit" moment that sparks curiosity and makes others want to use the tool, creating a natural viral effect.
Team members learn the capabilities and best practices for using their own AI agents by observing others' interactions in public channels. This "mid journey dynamic" creates a tacit transmission of knowledge about what's possible, accelerating the entire organization's learning curve much faster than formal training.
Individual AI use is often a siloed, one-to-one experience. To foster collective learning, create a dedicated "AI Playground" Slack channel. This gives team members a space to share successful prompts, interesting outputs, and even failures, turning individual experimentation into a shared team asset.
To maximize an AI agent's effectiveness, treat it like a team member, not just a tool. Integrate it directly into your company's communication and project management systems (like Slack). This ensures the agent has the full context necessary to perform its tasks.
To drive adoption of AI agents, don't force users into a new application. Instead, integrate the agent directly into their existing collaboration tools like Slack. This approach reduces friction and makes the agent feel like a natural part of the team, leading to higher engagement and user satisfaction.